Part:BBa_K5102061:Design

mTagBFP2

Assembly Compatibility:

• 10
  COMPATIBLE WITH RFC[10]
• 12
  COMPATIBLE WITH RFC[12]
• 21
  COMPATIBLE WITH RFC[21]
• 23
  COMPATIBLE WITH RFC[23]
• 25
  COMPATIBLE WITH RFC[25]
• 1000
  INCOMPATIBLE WITH RFC[1000]

  Illegal BsaI.rc site found at 634
  Illegal SapI.rc site found at 16
  

Design Notes

The synthetic UTR was designed utilizing the deep learning model developed by Castillo-Hair et al., which optimizes 5’ UTRs for efficient mRNA translation using generative neural networks and gradient descent (refer to the model wiki for more details). This model was trained on polysome profiling data from randomized 5’ UTR libraries across multiple cell types, allowing it to learn sequence features that enhance translation efficiency. The model was validated by calculation of the mean ribosome load (MRL) and minimum free energy (MFE) for each designed UTR.

Source

The part has been amplified from an already existing plasmid in the lab.

References

Castillo-Hair, S. et al. Optimizing 5’UTRs for mRNA-delivered gene editing using deep learning. Nat Commun 15, 5284 (2024).